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Smart Magneto-Adaptive Resilient Technology for nonlinear vibration control of complex structures under Multi-hazard conditions

Project description

More resilient infrastructure with smart non-linear vibration control

Europe’s infrastructure including roads, bridges and offshore energy structures faces growing threats from vibrational forces associated with earthquakes, wind, waves and traffic. Conventional vibration control systems often fail under complex, highly non-linear, real-world conditions. With the support of the Marie Skłodowska-Curie Actions programme, the SMART-M project aims to develop a next-generation adaptive damping system combining magnetorheological elastomers (materials whose mechanical properties change in a magnetic field) with high-damping rubber bearings and intelligent deep learning control algorithms. This hybrid system will enable real-time vibration mitigation and structural health monitoring. Validated through accelerated aging tests and life-cycle assessment, the system could enable safer, more durable and cost-effective infrastructure resilient to multiple climate and seismic hazards.

Objective

The global demand for resilient vibration control technologies in civil, bridge, and offshore infrastructure is rapidly increasing due to complex multi-hazard environments. Conventional damping systems often fail under highly nonlinear excitations, as demonstrated by historical infrastructure failures such as the Morandi Viaduct bridge collapse and offshore wind turbine damage. The SMART-M project addresses this urgent need by developing a next-generation magneto-adaptive resilient technology that integrates magnetorheological elastomers (MRE) with high-damping rubber bearings (HDRB), enhanced by intelligent, data-driven control algorithms. This combination enables real-time adaptive vibration mitigation, structural health monitoring, and long-term resilience against wind, seismic, traffic, and wave-induced excitations.
The project will design and optimize the hybrid system using nonlinear finite element simulations with reduced-order models for MRE-based damping systems, enabling efficient, accurate predictions and robust optimization validated against experiments. Deep reinforcement learning (DRL) and physics-informed neural networks (PINN) will be employed to deliver for real-time vibration control and condition monitoring of advanced nonlinear vibration control in complex structure. A multi-mode damping architecture will allow seamless transitions between passive, semi-active, and active control, ensuring energy-efficient performance. Long-term durability and sustainability will be validated through accelerated aging tests and a life-cycle assessment.
SMART-M will set a new benchmark in learning-enabled vibration control, supporting EU seismic risk policies and the Mission “Climate Adaptation”, while ensuring safer, sustainable structures and reducing maintenance costs. It delivers a transformative solution aligned with the MSCA Green Charter and Horizon Europe mission-driven innovation goals for climate-resilient, digitally enabled, and safe built environments.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSITA POLITECNICA DELLE MARCHE
Net EU contribution
€ 209 483,28
Address
PIAZZA ROMA 22
60121 Ancona
Italy
Region
Centro (IT) Marche Ancona
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data